This disclosure relates generally to patient monitors and physiological sensors used for acquiring electrophysiological signals from a subject/patient. More particularly, the disclosure relates to validation of a physiological sensor connected to a patient monitor.
A prerequisite of patient care is that accurate and reliable measurements can be made from the patient to evaluate the patient's state. Since a patient monitor connected to a sensor may perform rather complex calculations based on the physiological signals acquired through the sensor and since the results obtained may depend on a variety of parameters related to the sensor, it is important that the sensor fulfills certain quality standards and is thus authorized to be used in the patient monitor for the measurement in question. The use of aged, damaged or low quality sensors may lead to inaccurate and/or unreliable results, which may in turn contribute to incorrect medical decisions and even risk patient safety.
In terms of patient safety, die use of non-authentic unauthorized and/or counterfeited sensors is also to be prevented, since the cooperation of such sensors with the patient monitor is not tested and the sensors therefore involve the same risks as authentic but aged or low quality sensors.
It is therefore common practice to provide a sensor/monitor system with a detection mechanism that detects aged and/or unauthorized sensors, or with a mechanism that tends to improve the performance level of the sensor. The solutions may be classified into different categories according to the type of data stored in the sensor and according to the way in which data stored in sensor memory is employed. Typically, the content of the sensor memory is used by a monitor algorithm to make the measurement more accurate. For this, the sensor memory may hold sensor parameters that are relevant to the measurement. The sensor parameters are typically variables that the patient monitor is incapable of measuring, such as LED wavelengths. The sensor memory may also hold operating parameters that prevent the use of the sensor outside a safe operating range. A further solution is to record other information related to the use of the sensor into the sensor memory, such as total usage time, manufacturer identification, expiration data, or warranty date of the sensor. A still further solution is to use the sensor memory content to upgrade the software in the oximeter monitor itself in order to improve the accuracy and/or performance or to update the functionality of the patient monitor.
Although current solutions can prevent the use of sensors that may compromise patient safety, these solutions cannot achieve their objectives without detracting from the yield of the manufacturing process. In the manufacturing phase, several parameters are currently measured from the sensors manufactured. These parameters are used in quality control to monitor the quality of the manufactured sensors and to identify the sensors that may not function properly in the monitor. Due to the inherent variability of the manufacturing process, which inevitably results in variability in sensor parameter values, wide enough acceptance criteria are generally necessary for the sensor parameters to ensure an adequate process yield. This is significant especially when manufacturing disposable sensors, due to the tighter cost requirements compared to reusable products. However, as patient safety cannot be compromised, the acceptance criteria have to be tight enough to ensure patient safety. That is, the requirement of patient safety is contradictory to the pursuit of high manufacturing yield.
Consequently, the requirement of patient safety translates into the above-mentioned tight acceptance criteria for the sensor, which in turn detracts from the yield of the manufacturing process and thus also increases the product costs.